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Statistical analysis of data - Statistics Project Example

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Here data ofpollutant emission for three kind of construction activity: Buildings and building construction works, Constructions and construction work for civil engineering and the Specialised construction works has been…
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Statistical analysis of data
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Data Availability: Construction activity causes environmental pollution. Here data ofpollutant emission for three kind of construction activity: Buildings and building construction works, Constructions and construction work for civil engineering and the Specialised construction works has been reported. This data is a time series data where the emissions of pollutants (in thousands of tonnes) have been recorded from 2000 to 2009 from various constructional activities. Pollutants have been categorized into four categories- Greenhouse gases, Acid rain precursors, heavy metals and other pollutants.

Data Analysis:In this dataset we can find out the average emission of the pollutants over the years for different activities and can report which activity has the most notorious impact on the environment. As we have analysed Constructions and construction works for civil engineering has the highest average emission of greenhouse gases, heavy metals and acid rain precursors compared to others while specialised construction works has the highest average emission of other pollutants. For the year 2009 and for other years also we can find out which construction activity has created the maximum and minimum pollution and thus which is sustainable and which is not.

Since 2005 to 2009 we can see that a specialised construction service has created the maximum pollution and thus is less sustainable while the Buildings and building construction works has created the minimum pollution over the years and thus is more sustainable than others. From 2000 to 2004 activity of constructions and construction works for civil engineering has created the maximum pollution. Time series forecasting of overall emission for three activities can be given for the next 5 or 10 years using minitab or other statistical tools like R or SAS.

In excel we can do moving average and trend analysis like linear trend, quadratic trend etc for the data.Data weakness and Data Requirement:In the given data, it has been noticed that the data for year 2000 and 2001 is exactly same across all categories. Data on other manufacturing sectors and industries like automobile industry, chemical industry, fertilizer industry etc and their emissions of pollutants like greenhouse gases can also be collected for time period say 2000 to 2013 so as to compare it with the construction activity emissions of the same.

Time series analysis can be done in tools like minitab to forecast each sector emission of greenhouse gases for next five years. Time series forecast like moving average, blended moving average, trend analysis can be done in excel too. Air pollution index can be collected for a particular country and along with it the emission from construction activities and other sectors or industries can be collected for that country for the period of 2000-2009 and the causal effect can be estimated by running a regression model in excel where the air pollution index will be the dependent variable and the emission from construction activities as the independent variable.

We can determine thus that what is the significance of the emissions from construction activity has on air pollution.ReferenceYi, Q. (2009).Point Sources of Pollution: Local effects and their control. Eolss Publishers.Available at: http://www.eolss.net/Sample-Chapters/C09/E4-11-02-01.pdf (accessed on January 17, 2015)

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